All things Big Data, Hadoop, and NoSQL

Dale Kim

Dale is Director of Industry Solutions at MapR. His technical and managerial experience includes work with relational databases, as well as non-relational data in the areas of search, content management, and NoSQL. Dale holds an MBA from Santa Clara University, and a BA in Computer Science from the UC Berkeley.

NoSQL: Filling the Gaps in Your Traditional Relational Database
With the many different characteristics of NoSQL databases available today,
it's not always clear how to best categorize the different NoSQL offerings.
Typically, though, NoSQL databases are labeled according to the associated
data model, most commonly: key-value, wide-column, document, and graph. But
more important than the differences between them are the reasons why they are
growing in popularity as a whole. In general, NoSQL databases are meant to
fill some of the capability gaps found in traditional relational database
management systems (RDBMS).
Today's web-based applications are highly demanding, so the databases that
hold their vast stores of information are not only expected to be very
flexible in nature (supporting various data formats), but also to manage
extreme performance and scaling. Ente... (more)

NoSQL databases are highly scalable and capable of solving a wide range of
data problems, which make them great for supporting complex, unpredictable,
and large volumes of data. While still considered relatively young in the
enterprise software market--the current industry adoption is estimated at
20%--deployments can potentially double in 2017. This is reflective of the
growth of emerging use cases that require scalable and flexible systems. In
addition, organizations find that some of their applications currently
deployed on relational database management systems (RDBMS) are be... (more)

5 Ways the NoSQL Database World Has Matured Over the Years
With the proliferation of NoSQL databases in recent years, it can be easy to
forget that not long ago, we were all discussing how to optimize traditional
relational databases to perform tasks for non-relational workloads. Before we
were talking about cost-effective horizontal scaling, flexible data types,
and extremely fast data accesses, the world was all about the relational
database management systems (RDBMS).
To provide a quick recap of the long-running, pre-NoSQL years, RDBMSs
organized data into two-dimensional tabl... (more)

Apache Hadoop is an open source Big Data processing platform that comes with
its own extensive ecosystem to support various business and technical needs.
Hadoop's specialty is large-scale processing and analytics over volumes of
data that cannot be efficiently handled by traditional technologies. Hadoop
is often complemented by the class of database management technologies
referred to as NoSQL, which is also great for large volumes of data, but
NoSQL is more about fast reads and writes than about massive processing.
NoSQL and Hadoop can work together to tackle big data challenges... (more)

NoSQL Databases to Support Large Web Applications
NoSQL databases are powerful tools for supporting big data applications,
maximizing scalability, performance, and availability. Their unique features
and easy implementation render them well-equipped to meet a variety of
enterprise needs in a range of use cases.
NoSQL is a database technology that was developed to address critical issues
today such as a huge increase in data volume, a high frequency of data
access, and support for varying data formats. Relational database management
systems (RDBMS), on the other hand, were not des... (more)

Cloud Expo

Cloud Computing & All That
It Touches In One Location Cloud Computing - Big Data - Internet of Things
SDDC - WebRTC - DevOps
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